Project Grant 2438005
- This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CFDA 47.070) program aims to develop software frameworks that can efficiently serve and deploy machine learning models for a variety of AI-powered applications. The $600,000 award, spanning from October 2024 to September 2027, tasks the prime awardee, Georgia Tech Research Corporation, with creating agile mechanisms and policies to serve a family of AI models across...
- This $236,099 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program is supporting research to develop robust optimization and machine learning algorithms capable of handling dynamic and uncertain data environments. The research aims to advance optimization techniques for fundamental supervised learning tasks, yielding computationally and data-efficient algorithms with provable error guarantees. This work will...
- The National Science Foundation awarded a $600,000 Project Grant under its Computer and Information Science and Engineering program (CFDA 47.070) to the University of Florida to support research on the design and analysis of recursive algorithms with applications in machine learning, optimization, and reinforcement learning. The research aims to develop new techniques to ensure stability and accelerate the convergence of stochastic approximation algorithms, which are critical to training...
- This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program, with CFDA Number 47.070, will support a $599,963 research project by the University of Southern California (USC) from January 1, 2025 to December 31, 2027. The project will explore a new mathematical lens based in combinatorics, optimization, and graph theory to deepen the understanding of machine learning and guide the development of improved algorithms. The...
- This $600,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research at North Carolina State University to explore advanced sampling and optimization techniques for decentralized machine learning. The key objectives are to: Enhance the sampling efficiency of interacting nonlinear Markov chains through adaptive spatio-temporal repellency among multiple "self-repellent random walks",...
- This collaborative research project grant of $661,515, awarded by the National Science Foundation's (NSF) Division of Computing and Communication Foundations under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), supports fundamental research in optimization algorithms from October 1, 2025, through September 30, 2029. Georgia Tech Research Corporation will develop advanced optimization techniques addressing three primary research thrusts: analyzing the...
- This National Science Foundation (NSF) award under the Computer and Information Science and Engineering (CISE) program provides $300,000 over 3 years to conduct collaborative research on mathematical and algorithmic foundations of multi-task reinforcement learning. The research aims to address the data efficiency challenge of reinforcement learning, developing new techniques to require less data and computation when jointly learning multiple tasks versus learning each task individually. The...
- The National Science Foundation awarded a $174,187 two-year Project Grant to Worcester Polytechnic Institute under the Computer and Information Science and Engineering program (CFDA #47.070). The grant supports research into optimization and sampling algorithms with provable generalization and runtime guarantees, and their applications to deep learning. The Computer and Information Science and Engineering program aims to advance computing and communication sciences through investigator-initiated...
- The National Science Foundation awarded a $700,000 Project Grant to the Georgia Tech Research Corporation from July 1, 2021 to June 30, 2024 under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The grant funds collaborative research on developing Markov chain algorithms to solve problems in computer science, statistical physics, and self-organizing particle systems. The Computer and Information Science and Engineering program supports...
- This Project Grant award of $160,673 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research to combine algorithms and machine learning to improve decision-making under uncertainty. The project, led by New York University (NYU), will explore incorporating machine-learned predictions into algorithm design as well as developing learning models optimized for specific algorithmic objectives. This work aims to create a...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) (CFDA 47.070) Project Grant award of $108,000 to the Georgia Tech Research Corp, Office of Sponsored Programs, will fund collaborative research to develop a unified framework for analyzing adaptive stochastic optimization methods for machine learning applications. The research aims to produce self-tuning optimization algorithms with rigorous guarantees to reduce wasteful computation required by current techniques. The project will also extend these algorithms to handle imperfect data or information such as biased functions, corrupted data, or novel approximation techniques. The goal is to provide researchers and practitioners with easy-to-use tools for designing next-generation algorithms for cutting-edge machine learning applications. The award period runs from July 1, 2024 to December 31, 2024.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $108.0k | 8/5/24 |